A transitional response high-fit predictive framework for container vessel contingency reroute

Abstract

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Supply chain disruptions affect shipping service reliability, operations efficiency and carbon emissions. In disruptions like Red Sea Crisis, shipping lines struggled to anticipate the effectiveness of rerouting decisions while minimising shipping costs and emissions. A novel transitional response regression model (TRRM) within a three-stage high-fit predictive framework is developed, providing decision supports on rerouting and evaluating its environmental impacts. The model applies in the Red Sea Crisis with a longitudinal analysis across Asia-Europe trade services with rerouting via Cape of Good Hope, identifying key predictors, including vessel speed changes and number of port changes, from over fifty predictors. It provides improvement on a three-target measure of industry service reliability, container throughput and carbon emission mitigation by up to 85 %, with recommended reroutes with a lower emission increase rate from 47 % to 21 %. The model enhances emergency rerouting decisions with predictive insights in balancing service reliability, operations efficiency and emissions under the geopolitical uncertainty.